How Observability and AI Support DevOps’ New Way of Working
In this article, see how observability and AI support DevOps' new way of working.
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Throughout the last few years, the traditional tasks of a DevOps practitioner have evolved to focus less on keeping the lights on and more on adding value to the customer experience. This, in part, is because automation has taken over some of the mundane, daily tasks presented by old monitoring systems. But new solutions have emerged that support the new way of working for DevOps practitioners — bring in intelligent observability, or observability and AI.
Observability takes data from complex environments to infer from the outside what’s happening on the inside, i.e.: giving developers insight into what’s happening and where. But that’s not enough information to show what action needs to be taken, who is responsible, and how to prevent future incidents. With observability and AI, or intelligent observability, DevOps practitioners experience a whole new way of working. They can automate system monitoring, act quickly on insights into the issues that need attention, and understand what needs to be done to resolve incidents because they now understand why they happen.
Observability data needs AI. Here are three examples of how observability and AI create a new way of working for DevOps practitioners:
Enhances Trust and Transparency
Everyone has a role to play when a system fails — but if they don’t have proper tools in place to define what action needs to be taken and determine who owns that action, it becomes a finger-pointing game of “who did it.” With observability and AI, dev teams have full transparency into what’s happening and where the data is coming from. They can quickly learn where issues began and how to fix them without having to guess “who messed up.” As a result, teams build a new level of trust as they work together to resolve issues from the start.
Transparency and trust don’t stop at the team level — it has an impact at the executive level, too. When internal stakeholders have a clear insight into the development process and can see the impact it has on the business and its customers, it improves others’ perception of the dev team and proves their value to the business as a whole.
When DevOps practitioners are bogged down with the toil of managing alerts, they quickly experience burnout. Imagine a hamster wheel that is always turning with no definitive end in sight. This is how exhausted DevOps practitioners feel when they’re constantly in reactive, fire fighting mode.
In the new way of working, observability and AI empower DevOps practitioners to automate away toil and do what they truly love — collaborate to find solutions and innovate the product to create added customer value. Decisions become data-informed rather than opinion-driven, mitigating any disagreements or toil and emphasizing collaboration. When teams feel valued and trust each other, they experience less burnout and they gain more fulfillment from their roles.
Empowers Practitioners to Prove Their Value
Everyone has their own way of defining value, but it’s essential DevOps practitioners understand what value they bring to the table and how to get there. Antiquated tools hinder the ability of DevOps practitioners to show their value internally and externally. Sure, these tools aggregate data and provide visuals, but that’s it. And what value do pretty visuals of meaningless data bring to customers? They’re lacking insight into what action needs to be taken to determine what’s going on, where it’s happening and how to fix it.
With observability and AI, algorithms automatically create actionability from mounds of data, and DevOps practitioners have more time to add value to the customer experience — to incorporate feedback into the product, providing a direct business impact that creates a framework through which DevOps practitioners can tell their value story to stakeholders. When AI is applied to monitoring systems, DevOps practitioners are free to spend that time innovating and improving the customer experience. When the customer experience is improved, businesses see a positive impact on customer retention and, in turn, their revenue.
With intelligent observability, the possibilities are endless for DevOps practitioners. By investing in this sort of modern monitoring technology, they can escape the endless hamster wheel, improve their internal culture, and show their value internally and externally.
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